Estimation of Population Parameters
Aim
Undertake a small-scale survey to estimate population parameters.
Size of Sample
The size of the sample must be quite small, because it is stated so in
the aim. However, to make accurate estimates of population parameters
the sample must be large enough.
[IMAGE]
According to the Central Limit Theorem:
n If the sample size is large enough, the distribution of the sample
mean is approximately Normal.
n The variance of the distribution of the sample mean is equal to the
variance of the sample mean divided by the sample size.
These are true whatever the distribution of the parent population. The
Central Limit Theorem allows predictions to be made about the
distribution of the sample mean without any knowledge of the
distribution of the parent population, as long as the sample is large
enough.
For this reason, the sample size will be set at 50, which I consider
large enough for the distribution of its mean to be normal (according
to the Central Limit Theorem). It should not be larger because the aim
of this investigation is to carry out a “small scale survey”
How / What Data to be Collected
The sample will be of the weight of 50 smarties. To be a “good”
sample, that is that the results are valid and not biased in any way,
these smarties must be collected randomly. 10 tubes of smarties will
be bought, each from a different shop, and 5 will be selected at
random from each tube to be used in the survey. This should produce a
random sample.
The sample must be random for the Central Limit Theorem to be in
effect, so that the distribution of its mean is Normal and predictions
can be made about it, even though the distribution of the parent
population of smarties is unknown and not necessarily Normal.
What Calculations will be Made Using the Data
n The mean, standard deviation and variance of the sample.
n These will be used to estimate the variance and standard deviation
The question that was proposed for investigation was: Can the theoretical, actual, and percent yields be determined accurately (Lab Guide pg. 83)?
Research the census data from 1790 and 2000. Submit a report comparing some of the information contained in the reports. For example, where was the demographic center of the country in each instance? How was ethnicity reported? How is census information used? What strikes you as the most interesting aspects of the reports?
Answer: The fact that an investigation of local restaurants was conducted in which 150 were selected randomly indicates that this is a sample. This sample indicates that out of the 150 randomly selected, 42% of this random selection out of the total population of restaurants possessed series health code violations.
List of the tests to be conducted, material to be tested, the location of sampling, the organization’s name that will perform the test, and the frequency of testing.
For sample 1, we subtracted 28.64(g) from 26.30(g) and got a mass of 2.34(g). We did the same process for the rest of the samples and got a mass of 5.84(g) (32.14(g) – 26.30(g)) for sample 2 and 7.49(g) (33.78(g) – 26.30(g)) for sample 3. We divided the mass of the each samples by their own volumes. For sample 1 we divided 2.34(g) by 3.14(mL) and got a density of .745(g/mL). We did the same process for the other samples and got .795(g/mL) (5.84(g)/7.35(mL)) for sample 2 and .797(g/mL) (7.49(g)/9.39(mL)) for sample 3. We then add up all the densities of the sample and then divided by 3 to get the average density, .779(g/mL). The identity of the unknown liquid (5) was cyclohexane which has a density of .792(g/mL). We had to calculate the percent experimental error just like the unknown metal. We took .779(g/mL) minus .792(g/mL) and then divided it by .792(g/mL). Then multiply the product by 100 and got -1.64% error.
concentrations of 10mM, 20mM and 40mM. What this finding tells us is that our manipulation
-If the number of animals recaptured in the second sample (n2) is less than 8, the estimation of the population is likely to be biased.
Due to the invisibility of the population, a sampling frame can not be developed. Without the ...
Sample number is 40 and total number of participants is 120. N/A represents that none of the participants within a sample reported particular side effect.
In my experiment, I will use an overall volume of 50 cm³ of 2moles of
If we consider appropriately sized sample groups, we must ask ourselves how we define appropriate. If it is a particular ratio, that ratio would have to be...
The key to good research is preparation, preparation, and preparation. Hence, the key to making good sampling choices is preparation. Trochim (2008) defines sampling as the drawing of a sample (a subset) from a population (the full set). In our everyday lives we all draw samples without realising it. For instance, when one decides to taste some unfamiliar food or drink that is some form of sampling. Williams (2003 74) posits that “Sampling is a search for typicality). On the other hand, (Clark: 2006 87) defines sampling as “a process of drawing a number of individual cases from a larger population”. According to (Chiromo: 2006 16), “a sample is a smaller group or subset of the population”.
Population Density and Distribution A Dot Distribution map is able to show the population density of very small areas. They don't show the country as a whole, but show the little regions where people are concentrated. So it is very hard to compare countries to each other. In the other hand, the Population Density maps are maps with countries that are shaded according to their population density as a whole.
c. Statistical Design: It concerns with the question of how many items are to be observed and how the information and data gathered are being
Divide the sum in the step 4 by the total number of observed values; that is, divide the sum by n (population size) or n-1 (sample size).